A Metagenomic Approach Does Not Elucidate Uremic Toxin Levels in Hemodialysis Patients.
Taft, D.; Quinones, J. M.; Moreno, M. L.; Fatani, A.; Suh, J.; Gorwitz, G.; Wang, Y.; Segal, M. S.; Dahl, W. J.
Show abstract
Blood levels of uremic molecules generated through gut microbial metabolism are associated with disease risk, reduced quality of life, and mortality in patients with renal insufficiency. Modulation of the microbiome may offer therapeutic potential. ObjectiveThis study aimed to elucidate the relationships between fecal microbiome and serum levels of targeted uremic molecules in adults undergoing hemodialysis and, secondarily, the role of relative macronutrient substrate availability. MethodsFecal microbiota was profiled by whole metagenome sequencing, serum p-cresyl sulfate (CS), indoxyl sulfate (IS), phenylacetylglutamine (PAG), and trimethylamine N-oxide (TMAO) were quantified by liquid chromatography-tandem mass spectrometry (LC-MS/MS), and dietary intake was assessed by three multipass-method 24-hr recalls. ResultsDifferences in gut microbiome associated with serum uremic toxin levels were not detected. Instead, the relative substrate availability for the microbiota, using dietary protein-to-fiber ratio, was significantly associated with uremia. Serum levels of IS (multivariate linear model, p=0.042) and TMAO (p=0.032) were positively associated with dietary protein-to-fiber ratio, but not CS (p=0.096) and PAG (p=0.44). ConclusionThe lack of association of fecal microbiome with serum uremic toxins suggests that hemodialysis patients possess sufficient microbial enzymatic capacity for the synthesis of these molecules and that, instead, microbially available substrate, protein vs. fiber, may be the primary driver of production.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Efficacy of Tenapanor in Managing Hyperphosphatemia and Constipation in Hemodialysis Patients: A Randomized Controlled Trial 93%
- The urinary microbiome in association with diabetes and diabetic kidney disease: A systematic review 92%
- Evidences of histologic Thrombotic Microangiopathy and the impact in renal outcomes of patients with IgA nephropathy 92%
Similar papers in this journal
- Contribution of Uremia to Ureaplasma-Induced Hyperammonemia 92%
- Bacterial growth-promoting properties of pooled urine and individual urines from post-menopausal women with or without a urinary tract infection can vary substantially 88%
- Comprehensive characterization of COVID-19 patients with repeatedly positive SARS-CoV-2 tests using a large US electronic health record database 88%
Similar papers in this journal
- Glomerular spatial transcriptomics of IgA nephropathy according to the presence of mesangial proliferation 91%
- Temporal and sex-dependent gene expression patterns in a renal ischemia-reperfusion injury and recovery pig model 90%
- AKI Risk Score (AKI-RiSc): Developing an Interpretable Clinical Score for Early Identification of Acute Kidney Injury for Patients Presenting to the Emergency Department 90%
Similar papers in this journal
- Ursodeoxycholic acid (UDCA) mitigates the host inflammatory response during Clostridioides difficile infection by altering gut bile acids which attenuates NF-κB signaling via bile acid activated receptors 88%
- Antibiotic-induced shifts in fecal microbiota density and composition during hematopoietic stem cell transplantation 87%
- Mechanical Stimuli Affect E. coli Heat Stable Enterotoxin-cyclic GMP Signaling in a Human Enteroid Intestine-Chip Diarrhea Model 86%
Similar papers in this journal
- Characterizing the microbiome of patients with myeloproliferative neoplasms during a Mediterranean diet intervention 90%
- ACE-2-like enzymatic activity is associated with immunoglobulin in COVID-19 patients 87%
- Short-chain fatty acid production by gut microbiota from children with obesity is linked to bacterial community composition and prebiotic choice 87%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.